{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from waterfallcharts import quick_charts as qc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8rFVqNkHlOfH+GRFbATdVJyQzswYuvBBuuAHWWAM+/nLlWCZPhq5dv3r+J5/A7rvDkCHw\nDU/T2Vo128UXEbOA2ZKWqVI8ZmZfddRR6ZrTZZfBEkvAW2/BjBkwYgRsvPHc506dCrvuCqecAr0a\nzpBmrUk516A+Bf4j6XJJg+u/Kh2YmVmjBg2CvfdOVXpHHAFduqT9++6bvl90ETz7LJx9NvTpA2ee\nWVio9vWUc/XwJty9Z2a1oq4OHn30q/uvuSZ9/5//SV/W6pVTJHGlpA7AWqS5+V7OS2CYmZlVTDkz\nSewA/Bl4lTSTRE9Jh0fEXZUOzszM2q5yuvj+D9gqIsYCSFqdNBbKCcrMzCqmnCKJKfXJKXsNmFKh\neMzMzIDyWlCjJA0Hriddg/op8GQevEtEuIDCzMxaXDkJajHgfWDLvD0B6ATsREpYTlBmZtbiyqni\nO6gagTQkqS8wiLQe1GURcXYT520E/BvYq9JLgJiZWfXU5KzkeYqli4B+wNrA3pLWbuK8c4B7qxuh\nmZlVWk0mKNKaU2Mj4rU85uo6YOdGzjsauBGo6Aq/ZmZWfbWaoLoDb5dsv5P3zSGpO7ArcElzDySp\nv6RRkkZNmDChxQM1M7PKaPIalKTjm7tjRPxfy4czX/4E/CoiZktq8qSIuBS4FKCuri6qFFujho4e\nyqVPXYokLuh3ARuusOGcY9c9fx0XjryQdmrH0h2X5tqfXMvSHZcuMFozs2I114JaKn/VAT8ntWC6\nAwOADZu5X0sYB6xcsr1S3leqDrhO0hvA7sDFknapcFwL7KOpHzH4icE8eOCDDNt1GMfcdcxcx3f7\nzm6MOHgEDx/0MBuusCFXP3t1QZGamdWGJltQEXE6gKSHgQ0jYkre/i1pJolKehJYU1JPUmLaC9in\nQXw9629LGgrcERG3VDiuBTZy3Eh69+hNh/Yd6NmlJ1OmT2HazGl0XCSt/NmhfYc55342/TPW6blO\nUaGamdWEcq5BfRMonRx2et5XMRExEzgKuAd4Ebg+IsZIGiBpQCWfu1ImTp1Il05d5mx3Xqwzk6bO\nvRLo5U9fzvcu+R6PvPUI63RzgjKztq2cgbpXASMl1S/zvgtwZeVCSiJiODC8wb4hTZx7YKXj+bq6\ndurKx198uRLo5C8m07XT3CuBHrLhIRyy4SGc++i5DHxsIOdue261wzQzqxnzbEFFxJnAQcBH+eug\niPhDpQNb2PTq3osRb41gxqwZvDX5LZbssOSc7j2AL2Z+Med258U6s/iiixcRpplZzSinBQWwOPBJ\nRPxVUjdJPSPi9UoGtrDp0qkLR2x0BFsO3RJJDOo7iNHvjea+V+/jxM1PZOCjA7n/9fuB1Nq6Yucr\nCo7YzKxYimi+8lrSaaSKuW9HxLckrQj8IyI2r0aALamuri5GjRpVdBgLpbUnbFp0CGV5odu/iw7B\nrElrPll0BOV5ZaOvd39JT0VE3bzOK6dIYlfgx8BnABHxLqn83MzMrGLKSVDTIzWzAkDSEpUNyczM\nrLwEdb2kPwOdJR0G/BO4rLJhmZlZW1fOcht/lLQt8AnwbeA3EXFfxSOrUb7WUhvPZ2YLv3kmKEnn\nRMSvgPsa2WdmZlYR5XTxbdvIvn4tHYiZmVmp5mYz/zlwBLC6pOdKDi0FPFbpwMzMrG1rrovvWuAu\n4CzgpJL9UyJiUuN3MTMzaxlNdvFFxOSIeAMYBEyKiDcj4k1gpqRe1QrQzMzapnKuQV0CfFqy/Snz\nWMXWzMzs6yonQSlK5kOKiNmUP4efmZnZAiknQb0m6RhJi+avY4HXKh2YmZm1beUkqAHAZqSVbd8B\negH9KxkUgKS+kl6WNFbSSY0c31fSc5L+I+kxSetVOiYzM6uecmaS+IC05HrVSGoPXEQag/UO8KSk\n2yLihZLTXge2jIiPJPUDLiUlTzMzWwg0Nw7qlxFxrqQLyBPFloqIYyoY18bA2Ih4LcdyHbAzMCdB\nRUTpWKzHgZUqGI+ZmVVZcy2oF/P3IhZQ6g68XbJd37XYlENIY7a+QlJ/cpdkjx49Wio+MzOrsCYT\nVETcnr9fWb1w5p+krUgJaovGjkfEpaTuP+rq6ppfndHMzGpGc118t9NI1169iPhxRSJKxgErl2yv\nlPfNRdK6pKU/+kXExArGY2ZmVdZcF98f8/fdgOWBYXl7b+D9SgYFPAmsKaknKTHtBexTeoKkHsBN\nwP4R8d8Kx2NmZlXWXBffQwCSzmuwdvztkip6XSoiZko6CrgHaA9cERFjJA3Ix4cAvwGWBS6WBDCz\nnDXuzcysdShnRoglJK1WUlHXE6j4su8RMRwY3mDfkJLbhwKHVjoOMzMrRjkJ6hfAg5JeAwSsAhxe\n0ajMzKzNK2eg7t2S1gTWyrteiohplQ3LzMzaunlOdSRpceBE4KiIeBboIWnHikdmZmZtWjlz8f0V\nmA5smrfHAWdULCIzMzPKS1CrR8S5wAyAiPicdC3KzMysYspJUNMldSIP2pW0OuBrUGZmVlHlVPGd\nBtwNrCzpGmBz4MBKBmVmZtZsglIaAfsSaTaJTUhde8dGxIdViM3MzNqwZhNURISk4RHxPeDOKsVk\nZmZW1jWopyVtVPFIzMzMSpRzDaoXsJ+kN4DPSN18ERHrVjIwMzNr28pJUNtXPAozM7MGmlsPajFg\nALAG8B/g8oiYWa3AzMysbWvuGtSVQB0pOfUDzqtKRGZmZjSfoNaOiP0i4s/A7kDvKsUEgKS+kl6W\nNFbSSY0cl6TB+fhzkjasZnxmZlZZzSWoGfU3qt21J6k9cBGp5bY2sLektRuc1g9YM3/1By6pZoxm\nZlZZzRVJrCfpk3xbQKe8XV/Ft3QF49oYGFuySOJ1wM7ACyXn7AxcFREBPC6ps6QVImJ8BeMyM7Mq\naW7J9/bVDKSB7sDbJdvvkMrd53VOd2CuBCWpP6mFRbdu3ejfvz/rrLMOvXv3ZsiQISyzzDKceOKJ\nnHrqqQCcd955nHzyyUyfPp1f/OIX3HLLLbz++uvssccejB8/ni0e+R6bbbYZq6yyCn/729/o0aMH\ne+65JwMHDqR9+/acd955HHfccQCcfvrpDBo0iEmTJnHYYYfxxBNP8Nxzz9GvXz8A7rrrLtZdd116\n9erFX/7yF7p27cqxxx7LaaedBsCf/vQnTjjhBGbNmsWJJ57I3//+d9566y323ntv3nzzTR577DF6\n9+7NCiuswPXXX0/Pnj3ZZZddOP/88zmqw1GcddZZnHDCCQCcccYZDBw4kMmTJzNgwAAeeeQRxowZ\nw0477cS0adO499572WCDDdhggw244oor6NatGz//+c/53e9+B8AFF1zA0UcfDcBJJ53E1Vdfzbhx\n49hvv/145ZVXeOKJJ+jTpw/LLrssN954I2ussQY77LADgwcPplOnTpx++un88pe/BOCss87izDPP\n5NNPP+XII4/k/vvv56WXXmKXXXZhypQp3H///dTV1bHOOutw5ZVXsvzyy3PIIYdw5plnfiWWU045\nhcsvv5z33nuPn/3sZ4wZM4ZRo0ax9dZbs9RSS3HLLbew1lprsfXWW3PRRRex5JJLcsopp3DyyScD\ncO6553LaaacxdepUjjnmGIYPH87YsWP5yU9+wsSJE3nwwQfp1asXa665JsOGDaN79+7sv//+nH32\n2V+J5Te/+Q2XXHIJEyZM4OCDD+aZZ57hmWeeYbvttqNjx47cfvvtX+tv75FHHmkVf3sdOnTw394C\n/u1t1Ur+9s645+v97ZVLqQFSWyTtDvTNy7ojaX+gV0QcVXLOHcDZETEib98P/CoiRjX1uHV1dTFq\nVJOHzcysCiQ9FRF18zqvnJkkijAOWLlke6W8b37PMTOzVqpWE9STwJqSekrqAOwF3NbgnNuAA3I1\n3ybAZF9/MjNbeJQzk0TVRcRMSUcB9wDtgSsiYoykAfn4EGA4sAMwFvgcOKioeM3MrOXVZIICiIjh\npCRUum9Iye0Ajqx2XGZmVh212sVnZmZtnBOUmZnVJCcoMzOrSU5QZmZWk5ygzMysJjlBmZlZTXKC\nMjOzmuQEZWZmNckJyszMapITlJmZ1SQnKDMzq0lOUGZmVpOcoMzMrCY5QZmZWU2quQSVFyAcLGms\npOckbdjEeddIelnS85KukLRotWM1M7PKqbkEBfQD1sxf/YFLmjjvGmAt4HtAJ+DQqkRnZmZVUYsJ\namfgqkgeBzpLWqHhSRExPJ8TwEhgpWoHamZmlVOLCao78HbJ9jt5X6Ny197+wN0VjsvMzKqoFhPU\n/LoYeDgiHmnsoKT+kkZJGjVhwoQqh2ZmZguqJhKUpCMljZY0GhgPrFxyeCVgXBP3Ow3oBhzf1GNH\nxKURURcRdd26dWvJsM3MrIKULuHUDkk/Ao4CdgB6AYMjYuNGzjsUOBjYOiKmlvnYE4A3WzDclrIc\n8GHRQdQgvy6N8+vSOL8ujavF12WViJhni6EWE5SAC4G+wOfAQRExKh8bDhwaEe9KmklKNlPyXW+K\niN8VEfPXJWlURNQVHUet8evSOL8ujfPr0rjW/LosUnQADeWqvCObOLZDye2ai93MzFpOTVyDMjMz\na8gJqjZcWnQANcqvS+P8ujTOr0vjWu3rUnPXoMzMzMAtKDMzq1FOUGZmVpOcoMzMrCY5QdWIPP7L\nmuHXyKqpsb83SX7P5KuvTaX+N/1i1wBJyuO/kPQDSW1+Zvb6P3hJK0nqJKlTRIST1JckbS+pd9Fx\nLIwa/E/uIKmvpPUiYnbRsRWtwWvzfUnfoEK5xAmqBpT8so8BBgPti42oeDkZ9QNuBE4GhklaMtpw\n2WlJ0pakxYF9gKWKjWrhVPI/eQTwv0BP4BlJ3ys0sII1SE5HAMOAm4GDJfVo6edzgqoRkrYFDgR6\nR8SbktaV9P2CwyqMpHWBP5CWUvkCWJ6SxN0WW1IlyXkZYCpwP2nRTsDdTy2h9O9KUk/gR8B2edeD\nwAulHxSqHmDBSpLTzsAWwHrAGcCGwM4tnaQ8XVBBSj+JZONJbzi/zn/32wKvSLo6IoYXEWPBZpNW\nU+4B7ALsFRGTJW0GPBkRMwqNrgD5DbE3MBDoAEwAlpX0WL79BU3M/G/lKXkDriNNsDoCOIX0RrxD\nRMySdLikOyKiTb7WuUtvf6BnREwH7pIUpMVmO0m6NiLeaYnn8ieuAjRoJi8jaWlgLGny21WAW0mT\n5b4BLF1UnEWQ1F3SisAnwG+Ay4EtI+I1SVsCxwJdi4yxmko/pecFpB8mJak9gJuA1YFtgOuBsyW1\nmdemUiTtA5wKTAd+AOwbEf0i4gtJe5F6OtqMhi3FiPgAOBOYIOmcvO9u4C5gReCzFnvuNtylX4gG\nyel40pvNEsAFEXF7/XFJuwMnAftExH8LDLniSn7mXqRPq6OAc4AdgROAQcA04LfAaRFxa1GxFkVS\nf9I6aTOAqyLiDUkrAP8AdgIWAz6NiCnNPIzNg6RdSH9310bEA5KWBR7NX7OBDUgrLPynwDALIelg\nYA1S4r6ClIwOA96PiF/nc5aIiBZLUG5BVVlJcvo56Y1lP+Aj4GZJh+U36u2BI0j/CAt1coI5BRE7\nkLqu3gP2BQ4FniG1ovYlXQf4dUTc2hb6/nMRRP3tY0gtpvtIfzMHSmoXEeOBD4ClImK8k1OLWIn0\noXHNXDk6kbQu3Z2kFsJP21Jyqr+uKWl/4BfAv4CNgAGk/HERsI7S4rGQlkhqMb4GVSWS1gMOiIgT\n8q4vgL2Aw4EA+gF3Svo8Iq7Ja7hMLCjcqsqfUo8Gfps/tW5PWoxySeDciPhnybkNr90tdHKy3k7S\necC7pJbT9qTuzQmki9IdldZEewFYtKhYFxa5XL8uIs6XNA3YFRgt6ZmImEzqTm0zJG0DvBgR4yQt\nAmwGnBkR90l6HDgN2C8ijsjJ6QOYq5CnRbgFVT3/Bf4oqVd+k/0r6Y2lL/CriLgPuBc4N5dTL7TJ\nSdK3Je0laWWA/LO+DXxHUvuIuIf0ifUoUgtzzie5NpCcdgTOAh6MiLdJ3UorkSrItgB2joiZwAFA\nv4g4NSJeLSre1qqkEq/+PXAV4FuSDo+IvwB3k7qbN26j1ZGrAovm96KZwGuk12L53FI/jfT/2jUi\nRkfEu5UIoi2+8FUlaTlJXSJiau6S+TVwR05S75CqrjbOYwpeAzaKiE+LjLmS8htDf+BqUjIeJGlJ\nYDSpxbQSQElKAAASzklEQVRFPnUUqXDkV5LWagsDJCUtT7rmdmhE3CJpsZyQhwIrAMMiYoakA0nd\nLWMKC7aVK/mgs2b+fg3wALC2pAERMRh4DDiGVDHZpkTEZaQPR5MlrQrcQirY2kHSasAPSR+wK1pN\n6y6+CspdNb8F3pD0SkScQmoRXEgagLobqYx1K1K/9z6V+iRSK/L1prtJ/fqnAv9HGoj7DUDAipIO\nJ12M/hFpdeWVgJeKibiqppH+4b+QtBhwUq5cnAJMAi5VGry8PrCbW07zr0GR0srA3ZJ+FxF/lXQj\nKRkdImmRiDg7f7j8otCgqyQX3fSIiCck7QrcBvye1HrvRaqo3QvYm9S4ObLS1z1dxVchkvqS3oAH\nksrHTwD6R8RUSR1In4pnRsQB+fxlcl93myDpFuCpiPi9pINI11U+JnWtdAT+SOpmuBTYLiLeKCjU\nqsmty+NJBSHrAP8kfYB5gTQW7L+kUfvtImJCUXG2Vg2S02p56EJfUsn0oIi4Kh+7E3gFOD0iPiou\n4uqS9E1SMvovaTD4HhHxQb7GdCjQKyLezcNAvoiISZWOyS2oCshjUYYDP8lVZxuTxqqcl6+xHJ67\naW6SNCwi9iON+1nolbxJnAn8OBePnEDq034d2Jz0JtyRVF6+W1tITjCndflnUtfSysCtETEN5pSZ\nP7cwX5ustJLk9AtgF0m7R8TdkmYDAyUtRaoi7UAqzmkTyan+fzIi3pd0EXA28MecnNpHxOlKA3Hf\nzN3tVWu5uwVVIZJ+RGoVHEhqDTwGXAbcALweEXtJWgJYZmHv1muM0mj0q0kDIY+LiD/n/YtHxOf5\n9jcj4v0Cw6wJkn5KGhO3h7v1vp5cLn0UsGNETMjX/SaRWqwDSdW1p0TEswWGWTUNWpV1QHdST8aN\nwBkR8aeScw8FHq7m0BcnqArK3QfDSeN3zs77liTNFLFHW/80LGkj0uS4u0XE+Dy2Z3b996LjK1q+\nJrAnaTDknhHxfMEhtToNhyVI+hlpUPPHwGqkMXb3ksbbzSY1tKYWEWuRJJ0A/Jg09vI1SRuQuphP\nBCYDO5CKd6qaMFzFV0GRpv/YHjhIUue8+6dAJ9Jo7LZuNKkSrXdpUnJymuNj0rWQnZ2c5l+D1sGe\nudX+Hmmg6SGkv72jgc6k4oDP20pyktSx5HZvYHfS39lruVvvGVKlXn9SodKgIoZ4+BpUheWBbccB\nIyRdTKqC6V/p6pfWIJdM/xlY1Enpq/Kb5Z1Fx9FalSSnY4GDgGci4h6lyXWnR8S03BX/PWChHdrR\nkKRvk2YjOSX/380CXo6Ij/PQhi9yknpW0lak/89CrpG7i69K8gDMm4ANIsLjV8yqIBfhDAG2jYhP\nlWbDn0qqjNydVKDzs2hb0xd1Iq0jtgrwPqkoZAipe+/tfM6+wLLARRExq7BYnaCqp7QAwMxaXiPX\nnDYgrSt2J6kQ4tukN+a9SZWzn9W/KS/slNZYOy0ifpK3B5MmfD2ANOXaLqSxT4vlfbtExIsFhQv4\nGlRVOTmZVU7DijRJqwPPAneQliUZFhE/BP4ObBYRL7WV5JS9AcyWdE3e/i1ptpYhpLXXziEtCros\n8OOikxO4BWVmCxlJRwL7AI+QFv7crGQ82d6kAfS7RMQrxUVZPQ0S91akYS/PRMShkpYhvR7dgJMi\n4r2GrdAiuQVlZgsNSZuSphDbnrRw3kfk+eIkbUKqSNujrSQnmKtY5ETSeLo7SBPjXp9nrzmTVCTy\nB6WZy2tmORu3oMxsoSCpO6l7ahNSEcD2wE65Wm/HiLgjz63XJmaIKJULI24Cjo2I/+ZhL38BPomI\nQ3JLqmOk1XJrhltQZtYq5bkL628fTFopIID/JQ0q3S4npwOAI9pScip9bep3kVbuXiNvf0JajXkH\nSZdExORaS07gcVBm1kqVdF3tDawLXBwRY3KJ9LWSfkl6U/4RqYS6zSSnktdmW9Jigh+QqhkvkjQp\nIh5XmrT6EuDK4qJtnrv4zKxVyRf6vwvMioiLJQ0D+pDm1xudz9mIlJimATdFxMtFxVsUSccAe5Am\nXz6INF3RtsDppCnY+gLbVHNuvfnlBGVmrUae3/Jc0nyW6wCfRsQBuXS6A7B3pBVg25wGLae1SKsB\n1C8nsg5pzstZeSaJjsDkiHizsIDL4ARlZq1CXrbmOlJ33UOSugFXAcdHxIuS7iBVo+0fERVd6bXW\nNEhOPUnzfR5KminiB8Dukdai+ynwUC1eb2qMiyTMrDWZBHRTWvF2Aml5jOUBImJH0swIfykwvqpr\nkJz2Ji0b8ippVeqjIuJHOTkdCBxBmrW9VXALysxqXv2bsKQ+pMUtLwPWI01dtGvpZMOSVm5jM0QA\nIGkAsCnwf3mi1/WA35HmHhwD7ExqfbaaeQedoMys5jUyG8LpwOLA1hExWVI7oF1buv4k6Yeka0xv\nk+bQ60uqytsmIh7Ig247kVpN44EnWluxiBOUmdWkPLnp9Ih4KW+XJqlepKXJLwHuLmo5iKJI2p70\n899BStSrk2Zn/yVwPFAXEW8UFmAL8TgoM6tVhwE9JP0qT+wa9QNQI+IJSacD55Oq94YVGWg1SdqQ\nNOHtNhExStKqpGTVKyL+IGlR4GFJW0XEqwWG+rW5SMLMakruriMijiZV5Z0kac28b06XT0Q8SFoR\n95ECwizSf4HXgZ8A5JZSR1KBCBFxOqna8U5JizQyq0Sr4S4+M6tJefqiHUgr3r4PHFZ/DaWWZtyu\nply9ODPPnXcvMIJUBLE+qVhkRsm5y0XEhwWF2iKcoMys5uSZxy8DNo2IKZIuIrUQToyIscVGV4yS\nSsb2ecDtMqRZIlaPiFXyOYsAsyNi9sKQxN3FZ2aFa6Qb6kPgFdKs5ETEkaSZyq+V9K0qh1coSVtI\n2rg+2eTk1D4vlfFjYLyks/KxmfUl9609OYETlJkVrEF13uK5ZfAO8DmwoaRl86nXkGbh/riYSAuz\nIXCzpLr6HSVJ6lPSsiK7STq7sAgrxF18ZlYTJB1PmpanJ3AKsBywC2mpckjrPO0dEa8XEmCB8irB\nxwD7RcSTJfvru/uWBrouDKXlpZygzKxwkn5EWsdpJ1IiOpI0xuklUgtibeCa+jFRC7vGrh9JOpY0\n6Hb/iBhZsr99RMyqdozV4HFQZlYLlgFG5/n1bpf0CfA30kwRfys2tOpq0OX5Q9Jrc29EDJI0HRgm\nad/6ltTCmpzA16DMrMqaGJfzOtBJUs9cSv0QcAtpqp42pSQ5HUNaKmMb4CFJm0XEJcAfgbskfb/A\nMKvCLSgzq5oGrYMBQA+gM3AGMAM4FhiTc9i2wFkFhVooSdsBuwJbkAYj/wg4VdIfIuLS3JJa6ItF\nfA3KzKqmZCzPfqQ5444C/gd4F7iUdP1pTaA7cEZEvFBYsFXU8JpTXo59BWBz4MCI2E7SX0lFJPtF\nxL8LCrWq3IIys4qTtDmweETcl3dtAlwUEY+RSqQvAH4bEbvl8ztGxLSCwq2qBq3Kb5EaDi8Db0o6\nAHgsn/owqbKxzVQx+hqUmVXDasClkrbJ26+SJoJdBubMu7doXiUXYHoBMVadpHYlyel40iSw9+WK\nPYAngC0kXUWq4DsuIt4rJtrqcwvKzCoqtxCuzteVzs/Xnm4DLgB2kvQ08B3SVEbTYeGYBaEc9bM+\nSPoBsBVQB3wXuELSDNIs7aeTBuOe1dpnJ59fvgZlZhUhqR/Qj7TE+DkRMV7S/qQ1i/YDBPwc6EYq\npT6uNa32+nVI+h7QNyIGSupJKgb5JrBjRHyWK/T+DFwXEX8sMtYiOUGZWYuTtC2pHHowaWn2zyPi\npHzsIFKBxEF5PaOlgUUjYmJhAVdRXq9pFWAy0C0iXshVewcD9wM3RsSkvCjjQGCXiJhUXMTFcYIy\nsxaVB5feCmwQEWMl7QHsCIwE7oqIVyX9jDTG54CIeKDAcKtK0k7A94HfA0sAlwNvR8Tx+Vhf4FlS\nkprYlopFGuMiCTNraR+SliFfI2//GphCmmPvn5LWiogrSa2oNwqJsAC5Vfl74PGImJWXqT8dWEbS\n2RFxOzCcVFr+47xwY5soFmmKW1Bm1uIkbURaUG8WcEREXJ/3n0MqhjigrRRCwJxW5W3AhhHx37xM\n+0YR8Q9J65EGKI+PiFMk9SVN+9RmqvWa4haUmbW4PE/cD4D2wKIlh94G2uL1lA9J0zatmltG15KK\nQwD+A5wPfEvSaRFxt5NT4haUmVVMSUtqAPAB6aL/gRHxfKGBFaBBq/KoiLiuZGaNdqRS+0kRMb7Q\nQGuIx0GZWcVExJP52stIYALQJyJeLDisQuTX4gekGSHqtZNUPyP5mIJCq1luQZlZxUlaG5iVp/Bp\n00paUidHxJCi46llTlBmZlWWB+I+CRwSEX8tOp5a5QRlZlYASRuQBjC3+VZlU5ygzMysJrnM3MzM\napITlJmZ1SQnKDMzq0lOUGZmVpOcoMzMrCY5QZmZWU1ygjIzs5rkBGVmZjXJCcrMzGqSE5SZmdUk\nJygzM6tJTlBmZlaTnKDMzKwmOUGZmVlNcoIyM7Oa5ARlZmY1yQnKapqk5SVdJ+lVSU9JGi7pWwv4\nWMdJWryZ45dJWjvf/nQ+H3t9STuUbP9Y0kkLEmcjj72WpNGSnpG0+gLcv9mfuxKUPCBp6QW8/4GS\nVizZfkPSco2ct6Ok332dWK12OUFZzZIk4GbgwYhYPSK+D5wMfHMBH/I4oNE3akntI+LQiHhhAR97\nfWBOgoqI2yLi7AV8rIZ2AW6IiA0i4tUFuH+TP3dTJC2yAM9Tagfg2Yj4ZAHvfyCw4rxOAu4Edqp2\nArbqcIKyWrYVMCMihtTviIhnI+KR/Al9oKTnJf1H0p4AkvpIelDSDZJeknRNPvcY0hvevyT9K5/7\nqaTzJD0LbJrvV1f/XJLOlzRG0v2SuuV9c86RtFz+ZN8B+B2wZ27p7JlbABfm84ZKGizpMUmvSdo9\n728n6eIc5325dbh76QuQW2XHAT8viXs/SSPzc/1ZUvu8/xJJo3LMp+d9jf7cJY+/u6ShJXEOkfQE\ncK6kJSRdkZ/rGUk75/PWKXn+5ySt2cjvbl/g1nz+qiW/ixfz72bxfOw3kp7Mv8dL8+9qd6AOuCY/\nR6f8mEdLejr/vtfKfw8BPAjsOK8/Jmt9nKCsln0XeKqJY7uRWi3rAdsAAyWtkI9tQHpTXxtYDdg8\nIgYD7wJbRcRW+bwlgCciYr2IGNHg8ZcARkXEOsBDwGlNBRkR04HfAH+PiPUj4u+NnLYCsAXpjbS+\nZbUbsGqOc39g00YeezgwBDg/IraS9B1gz/wzrQ/MIiUDgFMiog5YF9hS0rpN/NzNWQnYLCKOB04B\nHoiIjUkfFgZKWgIYAAzKz18HvNPI42zO3L+7bwMXR8R3gE+AI/L+CyNio4j4LtAJ2DEibgBGAfvm\n13NqPvfDiNgQuAT4n5LHHgX0LuNns1bGCcpaqy2Av0XErIh4n5RENsrHRkbEOxExGxhNSgKNmQXc\n2MSx2UB9ohmWn+/ruCUiZucuxPouyi2Af+T97wH/KuNxtga+DzwpaXTeXi0f20PS08AzwDqkxDe/\n/hERs/Lt7YCT8vM8CCwG9AD+Dfxa0q+AVUoSSKmuETGlZPvtiHg03y59PbeS9ISk/wA/zHE35ab8\n/Snm/p1+QHndgdbKfN1+ZrNKGgPsPs+zvmpaye1ZNP13/kXJm/G8RP4+ky8/2C22gDFpPu7XkIAr\nI+LkuXZKPUmtio0i4qPcbddUfFFyu+E5nzV4rp9ExMsNznkxdwP+CBgu6fCIeKDBOTMltcsfEho+\nJ0BIWgy4GKiLiLcl/baZmOHL17Dh73QxoLEkaa2cW1BWyx4AOkrqX79D0rqSegOPkK75tM/Xh34A\njJzH400BlirzudvxZXLcB6jvAnyD1IKBuZPn/Dx2vUeBn+RrUd8E+pRxn/uB3SV9A0BSV0mrAEuT\nksvk/Fj9montfUnfkdQO2LWZ57qHdN1H+bk2yN9XA17L3Ye3kroUG3qZL1t2AD0k1Xdh1r+e9cno\nQ0lLsuCv57eA58s811oRJyirWfkC+K7ANkpl5mOAs4D3SNV9zwHPkhLZL3M3WXMuBe6uLxaYh8+A\njSU9T+p6qi9l/iOpYOEZoLTs+V/A2vVFEuX9hNxIun7zAqnb62lgcnN3yF2EpwL3SnoOuA9YISKe\nJXXtvQRcS0p+9Rr+3CcBdwCPAeObebrfA4sCz+XX/vd5/x7A87nr77vAVY3c907mTrgvA0dKehHo\nAlwSER8DfyEll3uAJ0vOHwoMaVAk0ZSt8vPZQkbpPcDMiiBpyYj4VNKypBbg5mUk2pqXC1auioht\nJa0K3JELIVr6eb4JXBsRW7f0Y1vxfA3KrFh3SOoMdAB+vzAkJ4CIGC/pL1rAgbrzoQdwQoWfwwri\nFpSZmdUkX4MyM7Oa5ARlZmY1yQnKzMxqkhOUmZnVJCcoMzOrSf8P1j9Njs3eX+QAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10f7121d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "a = ['Bias', 'Age', 'Sex', 'Blood Pressure']\n",
    "b = [0.3, 0.6, -0.1, -0.2]\n",
    "\n",
    "plot = qc.waterfall(a,b, Title= 'Patient A', y_lab= 'Predicted probability', x_lab= 'Contributing features (path)',\n",
    "                   net_label = 'Final Prediction')\n",
    "plot.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
